To resist the wormhole attacks in wireless sensor networks (WSNs) and improve network performance, a wormhole attack detection strategy integrating node creditworthiness and path hops (WADS-NC&PH) was proposed. Based on the abnormal situations of the neighbor number of the nodes under wormhole attacks, the suspicious nodes whose neighbor number exceeded the threshold were screened, and the nodes in their exclusive neighbor set were allowed to communicate with each other. The number of path hops was recorded, and the path whose number of hops exceeded the wormhole threshold was marked as the path to be tested. The Bayesian trust model was utilized to calculate the direct trust value of the intermediate node on the path to be tested, and combined with the trust factors such as the number of neighbors, processing delay, node energy, and packet forwarding rate, the indirect trust value of the node was judged, thereby obtaining the comprehensive trust value of the node. By integrating the number of path hops with the comprehensive trust of intermediate nodes, the path trust evaluation of the path to be tested was calculated. Based on the path characteristics of the nodes attacked by wormholes, the trust threshold was set reasonably, and WADS-NC&PH was proposed to detect wormhole attacks in WSNs. Simulation results show that WADS-NC&PH had a significant effect on the detection of wormhole attacks. Even in the face of highly attacked networks, this strategy could still effectively detect wormhole attacks and remove false links, improving the security and reliability of WSNs.